AWS Lake Formation Reviews

We primarily use the solution as a cloud data warehouse.

The security of the solution is pretty good.

The solution has many features that are applicable to events such as audits.

The solution offers a lot of documentation online that users can use to help with troubleshooting or learning the systems. We rely on these materials when we need support.

The solution could make improvements around orchestration and doing some automation stuff on AWS front automation. It would be useful if we could use automation to build images and use hardened images which are CIS compliant. 

For AWS, currently, we are facing the challenge when previewing. On AWS, we have set up a scanner instance with a Nexus scanner. For some reason, the scanner instance has been set up on AWS so that if it's in one region or maybe if it is deployed on one subnet, the other subnet is not reachable within the same region. The scanner is not reachable to the different subnets. For example, if there is a subnet A where the scanner is deployed, and if we want to scan the subnet B within the same region, the scanner is not reachable due to the fact that it's in Subnet A. That's a problem we are currently facing and trying to troubleshoot that.

I've been using the solution for about three years at this point.

The solution is very stable. We haven't experienced issues such as bugs or glitches. AWS if very good, performance-wise. It doesn't crash or freeze.

I don't really have any insights into scaling the solution. It's not my area of expertise. I haven't attempted to scale yet, so I can't speak to its capabilities.

We have different project teams using the solution across the organization curently.

We've never dealt with technical support just yet. If there is a need, we might reach out. However, I can't speak to their level of service as we've never used them yet.

Each team in our organization has the option to work with whatever solution they like. Others might use Azure, for example. We, right now, use AWS which we find to be more agile and scalable.

Whichever solution a team chooses wold be based on their own unique requirements.

I wouldn't describe the initial setup as complex. It's pretty straightforward.

For deployment, you basically just download it and start working. It's easy.

We didn't really have a deployment strategy in place. We are at the start of all of this automation stuff. Right now, different project teams are using the cloud. It's new for them as well. We are trying to see how best we can try to get these images, hardened images, deployed in an automated fashion.

There is a dedicated team that handles maintenance on the product. Every product team is responsible for their own setup plan (subscription), and they maintain it. Maintenence might be five or ten people per 1,000 users. It depends on the team size. Eveyone is scattered all across the globe. It's pretty difficult to say which team is handling maintenance and how many are responsible for it as different teams are independantly using the solution. 

I'm not privvy to licesning information. I'm not sure how much the solution costs.

Our company does not have a business relationship with AWS. We're just a customer.

I'm not sure which version of the solution we're using.

The thing is that we are not forcing the end-user or the project team to deploy the application. They have the liberty to choose their own platform. Either they can go with AWS or they can go with Azure. Most of the projects which are deployed on non-Windows OS tend to go for AWS.

My area of expertise is more in the auditing of the security standards and maintaining the security requirements as per the industry standard. I'm more in a security architect kind of role.

Every solution has its pros and cons, however, for our purposes, this solution works quite well for us.

I'd rate it overall at eight out of ten.

We use AWS Lake Formation typically for the data warehouse.

Customers choose to go with AWS Lake Formation because it's a cloud-based solution, and customers don't want to invest in on-premises hardware and software.

AWS Lake Formation's pricing could be cheaper.

I have been working with AWS Lake Formation for two years.

AWS Lake Formation is a stable solution.

AWS Lake Formation is a scalable solution. Our customers are mostly medium to enterprise-level businesses.

AWS Lake Formation's technical support is good and satisfactory.

Positive

AWS Lake Formation is a bit expensive.

My advice to users is that they first need to know what they want to achieve out of AWS Lake Formation. They need to have a clear-cut expectation from the solution, and they should involve a knowledgeable partner.

Overall, I rate AWS Lake Formation an eight out of ten.

We primarily use the solution in order to build infrastructure. It's basically for building network infrastructure.

The solution is quite good at handling analytics. It's done a good job at helping us centralize them.

We occasionally work with third-party libraries and they fail to integrate with this product effectively.

For the end-users, it's not as user-friendly as it could be. For example, if I have a Lake Formation return, once the code is in place, then working Lake Formation, or deploying Lake Formation code, still requires an engineer as opposed to being automated to the extent where end-users can actually deploy the whole infrastructure. 

The other issue is the debugging on the solution is not so straightforward. This should be simplified.

I've been using the solution for about a year and a half. It hasn't quite been two years. I haven't used it for that long.

The stability has come with time. At first, it wasn't so stable. We had some trouble and there was a bit of a learning curve. It gets easier and much more stable after you deploy.

While we are okay with the tooling, we're still working on the scaling process. Right now, there are no immediate challenges.

The solution isn't used by end-users. It's just used by our engineering staff who are working on the infrastructure.

Often, the people who handle the initial contact may or may not have the experience you need. It takes a while sometimes to get a person who can help. If it's a bigger issue, most of the time we have to engage the senior associates, and sometimes it takes time to find the right person. 

They also have hundreds of services there, and therefore, depending on where the problem is, finding the right person for the right service is an issue, due to the fact that, on the onset as an end-user, I don't know where the problem could be.

For example, while I may be working on the Lake at the surface, the problem may be on the Lake Formation. However, it could also be an EMR issue. Or it could be an issue in Spark, or it could be an issue within the EMR. and so on. That's why it's hard to get to the right person. You need to figure out the root cause then they need to figure out the best person to deal with the root cause.

That said, in terms of responsiveness, I don't have a problem with them. They do try to be helpful. It's just that the way the system is designed,getting to the right technical hand is complex and can take a while.

We didn't previously have another solution. Our instinct is to stick with internal solutions before moving out and looking for third-party options.

I would not describe the initial setup process as straightforward. There's definitely a learning curve involved. However, once you understand everything, it does get easier.

Once you deploy the solution, it stabilizes pretty fast and everything is a bit better from there onwards.

We're strictly customers of AWS. We're end-users.

I'm not sure which version of the solution we're using.

My advice to other organizations would be to not think of this solution as a one-time activity. It's an ongoing thing. It's a big change and there will new services and therefore it's constantly changing. You have to make sure that it's part and parcel of your everyday operations. 

The solution is pretty stable, or stable in the long run. However, every single day there is a need to grow the infrastructure, or there are new services being added externally and internally. You deploy more applications. You deploy more code. You deploy new libraries. You'll have to stay on top of everything to make sure it stays aligned with changes.

Overall, I would rate the solution at a seven out of ten.

In general, our clients use this as storage for raw data coming from systems. Our experience is that from the raw data you have to build up the data lake like a data warehouse. It's quite easy to pass from S3, for example, to Redshift. We used the data lake on AWS to store raw data and in some other cases to process advanced analytics. But the main use case here is storing raw data or archiving some data.

I would suggest using the entire ecosystem of AWS for this kind of job. The most important advantage of using AWS Lake Formation is its ability to connect the data lake to the other technologies in AWS. This is what I advise my clients.

Usually, you define an architecture in which you build up a data platform. The different technologies are different layers of that platform. My advice is to use the AWS technologies altogether. This can give a greater boost to the developer of the data platform.

In our experience what could be improved are not the support, performance or monitoring, but at a managerial level, the very expensive professional services of AWS. This could be an area of improvement for them. It's too expensive to acquire their support.

Generally, when you adopt a new technology, you always have to acquire a basket of professional services from the vendor. It's not only for system integrators, but also for clients because they always need some support. In this case, AWS is very expensive.

Something else they could improve is covering the end-to-end of the data platform with AWS products. They have to evolve. They have to improve the tools of data visualization a lot with QuickSight and ETS tool Glue. If they want to provide an end-to-end service with all the technologies to build up a complete data platform they need to improve these two technologies, these two solutions.

I have been using AWS Lake Formation for more or less one year.

We don't have our own projects. We are system integrators so we have projects based on customer requests.

AWS Lake Formation is stable.

AWS Lake Formation seems to be very scalable.

The initial setup is not so complex. There are no issues with deployment.

Also, because of the initial configuration, we usually ask for their support. Probably, for this reason we didn't have any trouble because they were able to do that. This is probably a reason the initial setup was not so complex.

On a scale of one to ten, I would give AWS Lake Formation a nine.

In our experience, this AWS solution is one of the main players now on the market in this field.

Additionally, because they can connect the offer in terms of infrastructure and software, sometimes you can combine the price and discount of infrastructure and software. This could be an advantage for clients.

My usual use cases for AWS Lake Formation involved securing and governing the data resources that we configured in AWS, but we did not use the analytics or machine learning capabilities specifically. For example, with the metadata in AWS Glue, we secured and governed that. For analytics output and Step Functions, we configured some permissions with AWS Lake Formation, but the roles themselves provided the general policy and interaction with other services.

We did not use it to share data internally or externally in terms of service across accounts, which made sense because it was specifically for a client where there was no interest in that particular solution.

Because of that, the orchestration and the way we used it was very limited. In fact, we rarely interacted with it because the main interaction, when configuring it for this generic type of form when solutionizing for a client, would be configuring and handling varying types of operations for RDS, creating a pool in Cognito, working more in SageMaker, configuring step functions with Lambda functions, and similar tasks.

The features and capabilities of AWS Lake Formation that I have found most valuable are that it is really convenient to see all the different data assets that were configured and understand who has and what type of service has or does not have access to those services.

Additionally, seeing which type of IAM roles or IAM in general are related to that type of configuration allows us to explore and error handle when we need to figure out if some policy was missing.

From a governance perspective, it adds significant value to figure out these types of things, though I must say there are better services in AWS overall for governance.

Regarding areas of AWS Lake Formation that could be improved or enhanced, I prefer not to answer, mainly because I do not believe that I would be the most valuable person to ask, as I have not used all of its different capabilities to the maximum to give an opinion.

Regarding optimization of the governance aspect of AWS Lake Formation in the future, people in general would prefer not to work with multiple tools that do nearly the same thing. I would rather have a tool that is specialized for governance and that is its sole purpose. Rather than creating an additional hundred tools, optimizing a tool to have a centralized location to do governance would be beneficial. Then users would not need to search extensively to figure out varying capabilities. Of course, there are some edge cases such as AI, where governance and guardrails might require different solutions. The general scope or principle is if you incorporate IoT or a lake house or do machine learning orchestration, you would rather simplify the scope instead of complicating it with many different types of services.

I have worked with AWS Lake Formation previously, and it was almost twelve months ago, but actually more six months ago.

AWS Lake Formation is very stable. I have never encountered any issues or locations or availability zones that went down. They are all very stable solutions.

AWS Lake Formation is very scalable for the use cases that I worked with, highly scalable for that matter. Because we used it for a very specific purpose, its full scalability capabilities were not fully tested. Since the orchestration of the solution is configured upon varying types of services and not AWS Lake Formation as a central location, I do not believe that in that orchestration it is really significant.

I have utilized AWS Lake Formation's fine-grained access control for data assets. Some data assets we have allowed access to, while others we have not configured. It depends on how you structure your solution. We have not used AWS Lake Formation for all the different types of data assets because varying types of clients require varying types of security considerations. It is mainly used with RDS Athena.

I was a customer of this service, and the company I worked for used it for the company itself. My interaction with it was creating a solution for a client.

I really love AWS and when compared with Azure, it is a bit more complicated overall, but AWS is significantly more robust, and you learn to appreciate that when you work with it and see how scalable it is. Maybe the UI is not entirely the best in the world, but it is very clear in its structure and there is always documentation that is really good that you can read about and figure things out.

This review rates AWS Lake Formation 5 out of 5.